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Abstract

Quantification of retroviral reverse transcriptase activity in retrovirus containing supernatant by quantitative reverse transcription PCR as a method for titration of HIV, lenti- and retroviral vectors is described here.. The procedure was optimized for use with LightCycler 480 (Roche, Vilvoorde, Belgium) and ABI 7300 real-time PCR system (reagents and procedures that are system specific will be marked accordingly in the protocol).

Table 2b. qRT-PCR reaction mix for use on ABI 7300 real-time PCR system (96 well plates)

1 sample

(n *1.1) samples

Eurogentec qPCR core kit for SYBR Green I

10.6 μl

10*(n*1.1) μl

Fwd primer (100 μM)

0.1 μl

0.1* (n*1.1) μl

Reverse primer (100 μM)

0.1 μl

0.1* (n*1.1) μl

MS2 RNA

0.1 μl

0.1* (n*1.1) μl

RNase inhibitor (10x diluted in H2O, final concentration: 4 U/μl)

0.1 μl

0.1* (n*1.1) μl

Lysis of the viral samples

Add 5 μl of the viral supernatant or standard curve per well of a 96W U bottom plate.

Add 5 μl of Lysis buffer/RNase mix to each well and mix.

Incubate 10 min at room temperature (RT).

Add 90 μl nuclease-free water to each well and mix.

Spin plate for 3 min at 1,600 x g at RT in table top centrifuge.

Keep the plate on ice until transfer to the 384W [LightCycler 480] OR 96W [ABI 7300] qPCR plate.

qRT-PCR

Take a cooling element out of the -20 °C and cover the cooling element with aluminium foil. Put the 384W [LightCycler 480] OR 96W [ABI 7300] plate on the aluminium foil during the filling of the plate to prevent evaporation.

Export the obtained Cq (Cycle of quantification) values from the LC480 or ABI Prism 7300.

Calculate for each sample the average Cq value of the duplicate measurements.

Make the standard curve: plot the average Cq value of SC1-SC7 versus the logarithm of the RT activity (expressed as mU RT/ml), determine the trendline and the formula expressing the correlation between the Cq values and the logarithm of the RT activity.

Use the obtained formula to calculate the absolute RT value of the samples.

Notes

Control samples:

Standard curve:
For absolute quantification of retroviral RT activity one can measure a serial dilution with known concentration of recombinant reverse transcriptase in parallel with the samples of interest (see a). Alternatively, a standard curve can be made by using serial dilution of a retro- or lentiviral supernatant of choice. In the latter case, it necessary to determine the RT activity of this supernatant in a first experiment by running a recombinant reverse transcriptase standard curve in parallel. For later experiment the serial dilution of the retroviral supernatant can be used as a standard curve (see b).

Use recombinant HIV Reverse transcriptase as standard curve
SC1 = solution of 200 mU/μl HIV Reverse Transcriptase. This is 1/50 dilution of the stock solution (10 U/μl)
SC2-SC7 are made by serial 1/10 dilution of SC1 in cell culture medium (preferably the same medium in which retro- and lentiviruses were produced)
Sample SC8 = cell culture medium (negative control)

Use high titer retroviral supernatant as a standard curve
SC1 = high titer retro- or lentiviral supernatant of your choice.
This sample can be any viral supernatant that is more concentrated than the samples being analysed. As mentioned above, the RT activity of this sample should be determined in an initial experiment by running a recombinant reverse transcriptase standard curve (see a) in parallel.
SC2-SC7 are made by serial 1/10 dilution of SC1 in cell culture medium (preferably the same medium in which retro- and lentiviruses are produced)
Sample SC8 = cell culture mediumAll samples are aliquoted per 8.5 μl in PCR strips. For each assay a new strip will be used.

Control samples C1, C2, C3:
3 retroviral supernatants of your choice that will be measured in each RT assay for quality control: The obtained RT activity of the control samples should be similar over different RT assays and offers a control for interrun variation.

The presented assay is an adapted version of the SG-PERT assay described before in Pizzato et al. (2009). This work was supported by SBO CellCoVir grant from the agency for Innovation by Science and Technology (IWT) Flanders, Belgium; HIV-STOP Interuniversity Attraction Poles program of Belgian Science Policy, European Union FP7 Health-2007-2.3.2-1 Collaborative Project iNEF, Ghent University grant BOF11/GOA/013 and grants from the Research Foundation – Flanders (FWO).

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